{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'boundingBox': '119,275,67,63', 'text': '沉'}, {'boundingBox': '187,272,67,66', 'text': '迷'}, {'boundingBox': '258,270,62,66', 'text': '学'}, {'boundingBox': '328,272,57,61', 'text': '习'}, {'boundingBox': '120,366,52,62', 'text': '日'}, {'boundingBox': '182,361,65,65', 'text': '渐'}, {'boundingBox': '251,359,63,66', 'text': '消'}, {'boundingBox': '318,357,66,66', 'text': '瘦'}]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 27785 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 36855 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 23398 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 20064 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 26085 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 28176 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 28040 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning: Glyph 30246 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 27785 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 36855 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 23398 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 20064 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 26085 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 28176 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 28040 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "C:\\Users\\Michael\\anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning: Glyph 30246 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0, 0.0, 1.0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import requests\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "# %matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Rectangle\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "\n",
    "endpoint = \"https://computervisiontest01.cognitiveservices.azure.cn/\"\n",
    "subscription_key = \"a73dc788ea304658a86d305400576ae5\"\n",
    "ocr_url =endpoint+\"vision/v2.1/ocr\"\n",
    "\n",
    "image_url = \"https://exp-picture.cdn.bcebos.com/b955ead0b503c8d239d0b1fa498333bf3aef2187.jpg?x-bce-process=image%2Fresize%2Cm_lfit%2Cw_500%2Climit_1\"\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': subscription_key}\n",
    "params = {'language':'unk','detectOrientation':'true'}\n",
    "data = {'url': image_url}\n",
    "response = requests.post(\n",
    "    ocr_url, headers=headers,params=params,json=data)\n",
    "response.raise_for_status()\n",
    "analysis = response.json()\n",
    "\n",
    "# Extract the word bounding boxes and text.\n",
    "line_infos = [region[\"lines\"] for region in analysis[\"regions\"]]\n",
    "word_infos = []\n",
    "for line in line_infos:\n",
    "    for word_metadata in line:\n",
    "        for word_info in word_metadata[\"words\"]:\n",
    "            word_infos.append(word_info)\n",
    "print(word_infos)\n",
    "\n",
    "# Display the image and overlay it with the extracted text.\n",
    "plt.figure(figsize=(5, 5))\n",
    "image = Image.open(BytesIO(requests.get(image_url).content))\n",
    "ax = plt.imshow(image, alpha=0.5)\n",
    "for word in word_infos:\n",
    "    bbox = [int(num) for num in word[\"boundingBox\"].split(\",\")]\n",
    "    text = word[\"text\"]\n",
    "    origin = (bbox[0], bbox[1])\n",
    "    patch = Rectangle(origin, bbox[2], bbox[3],\n",
    "                      fill=False, linewidth=2, color='y')\n",
    "    ax.axes.add_patch(patch)\n",
    "    plt.text(origin[0], origin[1], text, fontsize=20, weight=\"bold\", va=\"top\")\n",
    "plt.show()\n",
    "plt.axis(\"off\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
